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import logging
from typing import Dict, Any, List, Optional
import pandas as pd
# Configure logger for this module. Assumes logging is configured in app.py or main entry point.
logger = logging.getLogger(__name__)
def format_report_for_display(report_data: Optional[pd.Series]) -> str:
"""
Generates a complete Markdown string for a single report, including a dynamic title
based on the report's type and creation date.
Args:
report_data: A pandas Series representing a single row from the agentic analysis DataFrame.
It should contain 'comprehensive_analysis_text', 'report_type', and 'Created Date'.
Returns:
A Markdown formatted string for the report.
"""
if report_data is None or report_data.empty:
return "## Report Details\n\n*Please select a report from the library to view its contents.*"
# Assuming the main report text is in a column named 'comprehensive_analysis_text'
# You may need to adjust this column name based on your Bubble.io data structure.
report_text = report_data.get('report_text', '*Report content not found.*')
report_type = report_data.get('report_type')
created_date_str = report_data.get('Created Date') # Bubble's default field name
title = "Comprehensive Analysis Report" # Default title
try:
if report_type == 'Quarte': # As per your request for "Quarter" type
title = "Quarterly Insights Report"
elif report_type == 'Week' and pd.notna(created_date_str):
# Bubble dates are typically in ISO format, e.g., '2024-06-11T14:30:00.000Z'
created_date = pd.to_datetime(created_date_str)
day_name = created_date.strftime('%A') # e.g., 'Tuesday'
title = f"{day_name}'s Weekly Update Report"
except Exception as e:
logger.error(f"Error generating dynamic report title: {e}")
# In case of an error, the default title will be used.
return f"## {title}\n\n{report_text.strip()}"
def format_report_to_markdown(report_string: Optional[str]) -> str:
"""
Formats the comprehensive analysis report string into a displayable Markdown format.
This can be enhanced to add more structure if the report has implicit sections.
Args:
report_string: The raw text report from the orchestrator.
Returns:
A Markdown formatted string.
"""
if not report_string or not report_string.strip():
return "## Comprehensive Analysis Report\n\n*No analysis report was generated, or an error occurred during its generation.*"
# Simple formatting for now. Could be enhanced (e.g., looking for patterns like "Section X:" to make them H3)
# Ensure paragraphs are separated. Replace multiple newlines with double newlines for Markdown paragraphs.
# report_string_cleaned = re.sub(r'\n\s*\n', '\n\n', report_string.strip())
formatted_report = f"## Comprehensive Analysis Report\n\n{report_string.strip()}"
# You might add more sophisticated parsing here if your LLM output for the report
# has a consistent structure that can be converted to richer Markdown.
return formatted_report
def extract_key_results_for_selection(
actionable_okrs_and_tasks_dict: Optional[Dict[str, Any]]
) -> List[Dict[str, Any]]:
"""
Extracts Key Results from the OKR structure for UI selection in Gradio.
Each Key Result is given a unique ID for state management in the Gradio app.
Args:
actionable_okrs_and_tasks_dict: The dictionary representation of TaskExtractionOutput,
typically `orchestration_results["actionable_okrs_and_tasks"]`.
Expected structure: {'okrs': List[OKR_dict], ...}
Returns:
A list of dictionaries, where each dictionary represents a Key Result:
{'okr_index': int, 'kr_index': int, 'okr_objective': str,
'kr_description': str, 'unique_kr_id': str}
"""
key_results_for_ui: List[Dict[str, Any]] = []
if not actionable_okrs_and_tasks_dict or not isinstance(actionable_okrs_and_tasks_dict.get('okrs'), list):
logger.warning("No 'okrs' list found or it's not a list in the provided task extraction output.")
return key_results_for_ui
okrs_list = actionable_okrs_and_tasks_dict['okrs']
for okr_idx, okr_data in enumerate(okrs_list):
if not isinstance(okr_data, dict):
logger.warning(f"OKR item at index {okr_idx} is not a dictionary, skipping.")
continue
okr_objective = okr_data.get('objective_description', f"Objective {okr_idx + 1} (Unnamed)")
key_results_list = okr_data.get('key_results', [])
if not isinstance(key_results_list, list):
logger.warning(f"Expected 'key_results' in OKR '{okr_objective}' (index {okr_idx}) to be a list, got {type(key_results_list)}.")
continue
for kr_idx, kr_data in enumerate(key_results_list):
if not isinstance(kr_data, dict):
logger.warning(f"Key Result item for OKR '{okr_objective}' at KR index {kr_idx} is not a dictionary, skipping.")
continue
kr_description = kr_data.get('key_result_description') or kr_data.get('description') or f"Key Result {kr_idx+1} (No description)"
key_results_for_ui.append({
'okr_index': okr_idx, # Index of the parent OKR in the original list
'kr_index': kr_idx, # Index of this KR within its parent OKR
'okr_objective': okr_objective,
'kr_description': kr_description,
'unique_kr_id': f"okr{okr_idx}_kr{kr_idx}" # Unique ID for Gradio component linking
})
if not key_results_for_ui:
logger.info("No Key Results were extracted for selection from the OKR data.")
return key_results_for_ui
def format_single_okr_for_display(
okr_data: Dict[str, Any],
accepted_kr_indices: Optional[List[int]] = None,
okr_main_index: Optional[int] = None # For titling if needed
) -> str:
"""
Formats a single complete OKR object (with its Key Results and Tasks) into a
detailed Markdown string for display. Optionally filters to show only accepted Key Results.
Args:
okr_data: A dictionary representing a single OKR from the TaskExtractionOutput.
accepted_kr_indices: Optional list of indices of Key Results within this OKR
that were accepted by the user. If None, all KRs are displayed.
okr_main_index: Optional index of this OKR in the main list, for titling.
Returns:
A Markdown formatted string representing the OKR.
"""
if not okr_data or not isinstance(okr_data, dict):
return "*Invalid OKR data provided for display.*\n"
md_parts = []
objective_title_num = f" {okr_main_index + 1}" if okr_main_index is not None else ""
objective = okr_data.get('objective_description') or okr_data.get('description') or f"Unnamed Objective{objective_title_num}"
logger.info(f"OKR data desccr {objective}")
objective_timeline = okr_data.get('objective_timeline', '')
objective_owner = okr_data.get('objective_owner', 'N/A')
md_parts.append(f"### Objective{objective_title_num}: {objective}")
if objective_timeline:
md_parts.append(f"**Overall Timeline:** {objective_timeline}")
if objective_owner and objective_owner != 'N/A':
md_parts.append(f"**Overall Owner:** {objective_owner}")
md_parts.append("\n---")
key_results_list = okr_data.get('key_results', [])
displayed_kr_count = 0
if not isinstance(key_results_list, list) or not key_results_list:
md_parts.append("\n*No Key Results defined for this objective.*")
else:
for kr_idx, kr_data in enumerate(key_results_list):
if accepted_kr_indices is not None and kr_idx not in accepted_kr_indices:
continue # Skip this KR if a filter is applied and it's not in the accepted list
displayed_kr_count +=1
if not isinstance(kr_data, dict):
md_parts.append(f"\n**Key Result {kr_idx+1}:** *Invalid data format for this Key Result.*")
continue
kr_desc = kr_data.get('key_result_description') or kr_data.get('description') or f"Key Result {kr_idx+1} (No description)"
logger.info(f"KR data desccr {kr_desc}")
target_metric = kr_data.get('target_metric')
target_value = kr_data.get('target_value')
kr_data_subj = kr_data.get('data_subject')
kr_type = kr_data.get('key_result_type')
md_parts.append(f"\n#### Key Result {displayed_kr_count} (Original Index: {kr_idx+1}): {kr_desc}")
if target_metric and target_value:
md_parts.append(f" - **Target:** Measure `{target_metric}` to achieve/reach `{target_value}`")
if kr_type and kr_data_subj:
md_parts.append(f" **Key result type**: {kr_type}, for **data subject** {kr_data_subj}")
tasks_list = kr_data.get('tasks', [])
if tasks_list and isinstance(tasks_list, list):
md_parts.append(" **Associated Tasks:**")
for task_idx, task_data in enumerate(tasks_list):
if not isinstance(task_data, dict):
md_parts.append(f" - Task {task_idx+1}: *Invalid data format for this task.*")
continue
task_desc = task_data.get('task_description') or task_data.get('description') or f"Task {task_idx+1} (No description)"
logger.info(f"task data desccr {task_desc}")
task_cat = task_data.get('task_category') or task_data.get('category') or 'N/A'
task_effort = task_data.get('effort', 'N/A')
task_timeline = task_data.get('timeline', 'N/A')
task_priority = task_data.get('priority', 'N/A')
task_responsible = task_data.get('responsible_party', 'N/A')
task_type = task_data.get('task_type', 'N/A')
data_subject_val = task_data.get('data_subject')
data_subject_str = f", Data Subject: `{data_subject_val}`" if data_subject_val and task_type == 'tracking' else ""
md_parts.append(f" - **{task_idx+1}. {task_desc}**")
md_parts.append(f" - *Category:* {task_cat} | *Type:* {task_type}{data_subject_str}")
md_parts.append(f" - *Priority:* **{task_priority}** | *Effort:* {task_effort} | *Timeline:* {task_timeline}")
md_parts.append(f" - *Responsible:* {task_responsible}")
obj_deliv = task_data.get('objective_deliverable')
if obj_deliv: md_parts.append(f" - *Objective/Deliverable:* {obj_deliv}")
success_crit = task_data.get('success_criteria_metrics')
if success_crit: md_parts.append(f" - *Success Metrics:* {success_crit}")
why_prop = task_data.get('why_proposed')
if why_prop: md_parts.append(f" - *Rationale:* {why_prop}")
priority_just = task_data.get('priority_justification')
if priority_just: md_parts.append(f" - *Priority Justification:* {priority_just}")
dependencies = task_data.get('dependencies_prerequisites')
if dependencies: md_parts.append(f" - *Dependencies:* {dependencies}")
md_parts.append("") # Extra newline for spacing between tasks details
else:
md_parts.append(" *No tasks defined for this Key Result.*")
md_parts.append("\n---\n") # Separator between Key Results
if displayed_kr_count == 0 and accepted_kr_indices is not None:
md_parts.append("\n*No Key Results matching the 'accepted' filter for this objective.*")
return "\n".join(md_parts)
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